ACASA simulations and comparison with measured fluxes over Mediterranean maquis

Energy and mass fluxes between terrestrial ecosystems and atmosphere are widely simulated using land surface models. The "Advanced Canopy Atmosphere Soil Algorithm" (ACASA) model was used to estimate fluxes over a maquis ecosystem. The model accurately simulated wind speed and direction, air turbulence, energy fluxes, and mean scalar profiles within and above ecosystems (20 atmospheric layers). ACASA consists of an advanced scaling model from the leaf and soil level to the canopy level. The model employs a process-based interactive set of modules that include radiative transfer within the ecosystem, ecophysiological response of the vegetation to soil and atmospheric conditions, column water, snow and ice hydrology, and sophisticated interlayer turbulent transfer physics. Parameters were added to account for soil moisture stress, which is simulated with a soil water transport model. These linked models automatically yield carbon dioxide exchange and transpiration by accounting for stomatal control of evapotranspiration. Turbulent exchange between the layers and the atmosphere is described by a higher-order closure model, which allows counter-gradient transport that simpler models are unable to describe. ACASA requires (1) plant and soil characteristics, (2) 30-minute meteorological data, and (3) initial soil water content conditions. Input data came from in situ measurements or were selected from the literature when observations were unavailable. The aim of this research was to parameterize and validate the model over a sparse maquis canopy. ACASA flux outputs were compared with three years of field measurements over Mediterranean maquis near Alghero, Italy (Northwestern Sardinia). Different measurement periods were used to parameterize and validate the model. Net radiation and energy balance fluxes compared well with measured values. Differences between modeled and observed sensible (H) and latent (LE) heat fluxes were small. Both positive and negative CO2 flux simulations were well predicted by the model. ACASA captured the seasonal variation in Net Ecosystem Exchange (NEE) flux, including the summer decrease due to drought induced water stress. Therefore, ACASA showed good performances at predicting energy and mass fluxes between the atmosphere and the sparse maquis covered surface.